Kinetics of Mixed Microbial Assemblages Enhance Removal of Highly Dilute Organic Substrates

Our experiments with selected organic substrates reveal that the rate-limiting process governing microbial degradation rates changes with substrate concentration, S, in such a manner that substrate removal is enhanced at lower values of S. This enhancement is the result of the dominance of very efficient systems for substrate removal at low substrate concentrations. The variability of dominant kinetic parameters over a range of S causes the kinetics of complex assemblages to be profoundly dissimilar to those of systems possessing a single set of kinetic parameters; these findings necessitate taking a new approach to predicting substrate removal rates over wide ranges of S.     

Degradation of formaldehyde in packed-bed bioreactor by kissiris-immobilized Ralstonia eutropha

The ability of the Ralstonia eutropha cells to utilize formaldehyde (FA) as the only source of carbon and energy was studied in the kissiris-immobilized cell bioreactor (KICB) in batch-recirculation and continuous modes of operation. In batch-recirculation experiments, the test bacterium could tolerate concentrations of FA up to 1,400 mg/L at 30°C and aeration rate equal to 0.75 vvm (r _S = 7.25 mg/L/h, q S = 0.019 g_FA/g_cell/h). However, further increase of initial FA concentration resulted in degradation reaction of FA to stop at 1,600 mg/L. Results of continuous mode experiments showed that the biodegradation performance of the KICB was dependent on both feed flow rate and inlet FA concentration parameters. The optimum feed flow rate which corresponded to the highest biodegradation rate (r _S = 240.3 mg/L/h) was observed at Q = 18 mL/min when KICB did not operate under the external mass transfer limiting regime. Substrate inhibition kinetics (Edwards and Luong equations) were used to describe the experimental specific degradation rates data. According to the Luong model, the values of the maximum specific degradation rate (q _max), half-saturation coefficient (K _S), the maximum allowable FA concentration (S _m), and the shape factor (n) were 0.178 g_FA/g_cell/h, 250.9 mg/L, 1,600 mg/L, and 1.86, respectively.     

Kinetics of phenol degradation using Pseudomonas putida MTCC 1194

Pseudomonas putida (MTCC 1194) has been used to degrade phenol in water in the concentration range 100–1000?ppm. The inhibition effects of phenol as substrate have become predominant above the concentration of 500?ppm (5.31?mmoles/dm³). The optimum temperature and initial pH required for maximum phenol biodegradation were 30?°C and 7.00 respectively. From the degradation data the activation energy (E _a ) was found to be equal to 13.8?kcal/g mole substrate reacted. The most suitable inoculum age and volume for highest phenol degradation were 12?hrs and 7% v/v respectively. Surfactants had negligible effect on phenol biodegradation process for this microorganism. Monod model has been used to interpret the free cell data on phenol biodegradation. The kinetic parameters have been estimated upto initial concentration of 5.31?mmoles/dm³. μ _max and K _S gradually increased with higher concentration of phenol. However, beyond the phenol concentration of 5.31?mmoles/dm³, the inhibition became prominant. The μ _max has been to be a strong function of initial phenol concentration. The simulated and the experimental phenol degradation profiles have good correspondence with each other.     

CoMFA analysis of tgDHFR and rlDHFR based on antifolates with 6–5 fused ring system using the all-orientation search (AOS) routine and a modified cross-validated r2-guided region selection (q2-GRS) routine and its initial application

We report the development of CoMFA analysis models that correlate the 3D chemical structures of 80 compounds with 6–5 fused ring system synthesized in our laboratory and their inhibitory potencies against tgDHFR and rlDHFR. In addition to conventional CoMFA analysis, we used two routines available in the literature aimed at the optimization of CoMFA: all-orientation search (AOS) and cross-validated r²-guided region selection (q²-GRS) to further optimize the models. During this process, we identified a problem associated with q²-GRS routine and modified using two strategies. Thus, for the inhibitory activity against each enzyme (tgDHFR and rlDHFR), five CoMFA models were developed using the conventional CoMFA, AOS optimized CoMFA, the original q²-GRS optimized CoMFA and the modified q²-GRS optimized CoMFA using the first and the second strategy. In this study, we demonstrate that the modified q²-GRS routines are superior to the original routine. On the basis of the steric contour maps of the models, we designed four new compounds in the 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted pyrrolo[2,3-d]pyrimidine series. As predicted, the new compounds were potent and selective inhibitors of tgDHFR. One of them, 2,4-diamino-5-methyl-6-(2′,6′-dimethylphenylthio)pyrrolo[2,3-d]pyrimidine, is the first 6–5 fused ring system compound with nanomolar tgDHFR inhibitory activity. The HCl salt of this compound was also prepared to increase solubility. Both forms of the drug were tested in vivo in a Toxoplasma gondii infection mouse model. The results indicate that both forms were active with the HCl salt significantly more potent than the free base.     

Inhibition of the Fermentation of Propionate to Methane by Hydrogen, Acetate, and Propionate

Inhibition of the fermentation of propionate to methane and carbon dioxide by hydrogen, acetate, and propionate was analyzed with a mesophilic propionate-acclimatized sludge that consisted of numerous flocs (size, 150 to 300 μm). The acclimatized sludge could convert propionate to methane and carbon dioxide stoichiometrically without accumulating hydrogen and acetate in a propionate-minimal medium. Inhibition of propionate utilization by propionate could be analyzed by a second-order substrate inhibition model (shown below) given that the substrate saturation constant, K_s, was 15.9 μM; the substrate inhibition constant, K_i, was 0.79 mM; and the maximum specific rate of propionate utilization, q_m, was 2.15 mmol/g of mixed-liquor volatile suspended solids (MLVSS) per day: q_s = q_mS/[K_s + S + (S²/K_i)], where q_s is the specific rate of propionate utilization and S is the initial concentration of undissociated propionic acid. For inhibition by hydrogen and acetate to propionate utilization, a noncompetitive product inhibition model was used: q_s = q_m/[1 + (P/K_p)ⁿ], where P is the initial concentration of hydrogen or undissociated acetic acid and K_p is the inhibition constant. Kinetic analysis gave, for hydrogen inhibition, K_p(H2) = 0.11 atm (= 11.1 kPa, 71.5 μM), q_m = 2.40 mmol/g of MLVSS per day, and n = 1.51 and, for acetate inhibition, K_p(HAc) = 48.6 μM, q_m = 1.85 mmol/g of MLVSS per day, and n = 0.96. It could be concluded that the increase in undissociated propionic acid concentration was a key factor in inhibition of propionate utilization and that hydrogen and acetate cooperatively inhibited propionate degradation, suggesting that hydrogenotrophic and acetoclastic methanogens might play an important role in enhancing propionate degradation to methane and carbon dioxide.     

Microrespirometric characterization of activated sludge inhibition by copper and zinc

We have developed a novel microrespirometric method to characterize the inhibitory effects due to heavy metals on activated sludge treatment. This method was based on pulse dynamic respirometry and involved the injection of several pulses of substrate and inhibitors, of increasing concentration. Furthermore, we evaluated the inhibitory effects of heavy metals (copper and zinc), substrate and biomass concentrations, and pH on activated sludge activity. While higher biomass concentrations counteracted the inhibitory effects of both copper and zinc, higher substrate concentrations predominantly augmented the inhibitory effect of copper but no significant change in inhibition by zinc was observed. pH had a clear but relatively small effect on inhibition, partially explained by thermodynamic speciation. We determined the key kinetic parameters; namely, the half saturation constant (K _S ) and the maximum oxygen uptake rate (OUR _max ). The results showed that higher heavy metal concentrations substantially decreased K _S and OUR _max suggesting that the inhibition was uncompetitive.     

Effects of combining biological treatment and activated carbon on hexavalent chromium reduction

The objectives of the present work were: (a) to analyze the Cr(VI) removal by combining activated sludge (AS) with powdered activated carbon (PAC), (b) to analyze the effect of PAC and Cr(VI) on the growth kinetics of activated sludge, and (c) to determine if the combined method (AS-PAC) for Cr(VI) removal can be considered additive or synergistic with respect to the individual processes. Chromate removal was improved by increasing PAC concentrations in both PAC and AS-PAC systems. Cr(VI) removal using the AS-PAC system was higher than using AS or PAC. The increase of Cr(VI) caused longer lag phase and lower observed specific growth rate (μ_obs), biomass yield (Y_X/S), and specific growth substrate consumption rate (q_S) of activated sludge; additionally, PAC did not enhance the growth kinetic parameters (μ_obs, Y_X/S, q_S). Cr(VI) reduction in AS-PAC system was the result of the additive effect of each individual Cr(VI) removal process.     

Determination of enzyme kinetic parameters by continuous addition of substrate to a single reaction mixture and analysis by a tangent-slope procedure: I. Analysis of the method using computed progress curves

A new method has been developed which provides reliable estimates of enzyme kinetic constants from single reaction progress curves recorded under conditions of continuously increasing substrate concentration. Equally spaced data points simulating such progress curves and containing known amounts of superimposed random noise were fit to the Hill equation by (i) direct nonlinear curve-fitting of raw data, and (ii) a tangent-slope technique in which the raw data are numerically differentiated, transformed into substrate versus velocity data, and then analyzed as linear plots. Both integral and differential procedures provided accurate and precise estimates of the Hill parameters (S_0.5, V, and n) from single reaction mixtures. However, the tangent-slope method was at least 10-fold faster to compute and was not dependent on accurate initial guesses of the Hill parameters or integration of the rate equation. With the tangent-slope method, the optimal number of data points used in calculating tangent slopes was found to be 9 or 11. The reliability of the Hill parameters determined with the tangent-slope method was relatively insensitive to the maximum substrate concentration over a range of $\text{S}{}_{\mathrm{<mtext>max</mtext>}}\text{S}{}_{0.5}$ of 1.5 to 10; the optimal value was 3. Through further analysis of simulated data, it was found that slow enzyme inactivation (<4% loss during the assay), or product competitive inhibition (maximum product concentration < 30% of the inhibitor dissociation constant) does not produce serious errors in the Hill parameters. Methods are presented to detect and distinguish enzyme inactivation and product competitive inhibition. It is suggested that continuous addition methodology combined with tangent-slope analysis provides the basis for a flexible system for kinetic characterization of enzymes which has wider applicability and other advantages over multicuvette or conventional progress curve methodology. A major advantage in contrast to the progress curve approach is that product accumulation and associated product effects are lowest at lower substrate concentrations.     

Modeling of growth kinetics for Pseudomonas spp. during benzene degradation

A modeling study was conducted on growth kinetics of three different strains of Pseudomonas spp. (Pseudomonas aeruginosa, Pseudomonas fluorescens, Pseudomonas putida) during benzene degradation to determine optimum substrate concentrations for most efficient biodegradation. Batch tests were performed for eight different initial substrate concentrations to observe cell growth and associated substrate degradation using benzene-adapted cells. Kinetic parameters of both inhibitory (Haldane–Andrews, Aiba–Edwards) and noninhibitory (Monod) models were fitted to the relationship between specific growth rate and substrate concentration obtained from the growth curves. Results showed that half-saturation constant of P. fluorescens was the highest among the three strains, indicating that this strain could grow well at high concentration, while P. putida could grow best at low concentration. The inhibition constant of P. aeruginosa was the highest, implying that it could tolerate high benzene concentration and therefore could grow at a wider concentration range. Estimated specific growth rate of P. putida was lower, but half-saturation constant was higher than those from literature study due to high substrate concentration range used in this study. These two kinetic parameters resulted in substantial difference between Monod- and Haldane-type models, indicating that distinction should be made in applying those models.     

Application of an extended kalman filter method for monitoring high density cultivation of Escherichia coli

A real-time, on-line extended Kalman filter was used to describe and monitor the growth of Escherichia coli on glycerol. The growth of E. coli showed an inhibition kinetics with μ_max=0.806/h, K_S=0.68 g/l and K_i=87.4 g/l. As a feeding strategy, the conventional DO-stat with a DDC-PID control method, in which the dissolved oxygen concentration is maintained at a desired level by varying the substrate feedrate, was employed. The Kalman filter was based on an unstructured mathematical model and on-line measured data. The mathematical model comprised of mass balances of the biomass and substrate as well as kinetic and stoichiometric data which were measured prior to the process. For biomass concentration up to 50 g dry weight/l, the estimation of the process was rather accurate. At higher biomass concentration, product formation, indicated by an intense brown coloring of the fermentation broth, occured. Since the effect of this product on biomass production was not included in the mathematical model, the estimated data diverged from the experimental data at biomass concentrations greater than 50 g dry weight/l.     

Enhancement of the ozonation of wine distillery wastewaters by an aerobic pretreatment

The decomposition of the organic substrate present in wine distillery wastewaters (WDW) is studied in batch reactors, by an ozonation process, by an aerobic degradation and by another ozonation of the aerobically pretreated wastewaters. In the ozonation process, the effects on the substrate removal obtained of the temperature, pH and the presence of H₂O₂ and UV radiation are established, and an approximate kinetic study is conducted which leads to the evaluation of the apparent kinetic constants for the substrate reduction. In the aerobic degradation treatment, the evolution of the substrate, biomass and total phenolic compounds are followed during the process, and a kinetic study is performed by using the Contois model, which applied to the experimental data provides the specific kinetic parameters q_max and K₁. Finally, in the ozonation of the pretreated wastewaters, the?influence of the operating variables is established, and the effect of this aerobic pretreatment on the substrate removal and kinetic constants obtained in the ozonation stage is also discussed.     

Theoretical analysis of intrinsic reaction kinetics and the behavior of immobilized enzymes system for steady-state conditions

Mathematical modeling of immobilized enzymes under different kinetics mechanism viz. simple Michaelis–Menten, uncompetitive substrate inhibition, total competitive product inhibition, total non-competitive product inhibition and reversible Michaelis–Menten reaction are discussed. These five kinetic models are based on reaction diffusion equations containing non-linear terms related to Michaelis–Menten kinetics of the enzymatic reaction. Modified Adomian decomposition method is employed to derive the general analytical expressions of substrate and product concentration for all these five mechanisms for all possible values of the parameters Φ_S (Thiele modulus for substrate), Φ_P (Thiele modulus for product) and α (dimensionless inhibition degree). Also we have presented the general analytical expressions for the mean integrated effectiveness factor for all values of parameters. Analytical results are compared with the numerical results and also with the limiting case results, which are found to be good in agreement.     

Impact of initial conditions on extant microbial kinetic parameter estimates: application to chlorinated ethene dehalorespiration

Monod kinetics are the foundation of mathematical models of many environmentally important biological processes, including the dehalorespiration of chlorinated ethene groundwater contaminants. The Monod parameters—q _max, the maximum specific substrate utilization rate, and K _S, the half-saturation constant—are typically estimated in batch assays, which are superficially simple to prepare and maintain. However, if initial conditions in batch assays are not chosen carefully, it is unlikely that the estimated parameter values will be meaningful because they do not reflect microbial activity in the environmental system of interest, and/or they are not mathematically identifiable. The estimation of q _max and K _S values that are highly correlated undoubtedly contributes significantly to the wide range in reported parameter values and may undermine efforts to use mathematical models to demonstrate the occurrence of natural attenuation or predict the performance of engineered bioremediation approaches. In this study, a series of experimental and theoretical batch kinetic assays were conducted using the tetrachloroethene-respirer Desulfuromonas michiganensis to systematically evaluate the effects of initial batch assay conditions, expressed as the initial substrate (S ₀)-to-initial biomass concentration (X ₀) ratio (S ₀/X ₀) and the S ₀/K _S ratio on parameter correlation. An iterative approach to obtain meaningful Monod parameter estimates was developed and validated using three different strains and can be broadly applied to a range of other substrates and populations. While the S ₀/X ₀ ratio is critical to obtaining kinetic parameter estimates that reflect in situ microbial activity, this study shows that optimization of the S ₀/K _S ratio is key to minimizing Monod parameter correlation.     

Preparation of ACE-inhibitory peptides from milk protein in continuous enzyme membrane reactor with gradient dilution feeding substrate

In this study, a novel method of gradient dilution feeding substrate (GDFS) was established to improve the yield of angiotensin-converting enzyme (ACE) inhibitory peptides from milk protein. The hydrolysis process stability, enzymatic efficiency and kinetics of the method were studied and compared with traditional feeding modes, viz., adding water after feeding substrate or constant concentration feeding substrate. Results showed that the GDFS mode achieved the highest membrane flux and lowest fluctuation of protein concentration in the reactor. Moreover, the GDFS maximized protein conversion rate, yield of peptides, and ACE-inhibitory activity, with their values of 67.58 %, 138.51 g/(g*Neutrase), and 0.74 mg/mL (IC₅₀), respectively. In further study, the kinetic model of GDFS mode was successfully established with K_M of 69.481 g/L and V_max of 0.752 g·L⁻¹ min⁻¹. Based on the optimum condition of the kinetic model, the practical longest runtime was 720 min. Obtained results suggested that GDFS mode could be used as an alternative method in the preparation of high-yield bioactive peptides.     

Model of steady-state-biofilm kinetics

A steady-state biofilm is defined as one that has neither net growth nor decay over time. The model, developed for steady-state-biofilm kinetics with a single substrate, couples the flux of substrate into a biofilm to the mass (or thickness) of biofilm that would exist at steady-state for a given bulk substrate concentration. Based on kinetic and energetic constraints, this model predicts for a single substrate that a steady-state bulk concentration, S_min, exists below which a steady-state biofilm cannot exist. Thus, in the absence of adsorption of bacteria from the bulk water and for substrate concentration below S_min, substrate flux and biofilm thickness are zero. Equations are provided for calculating the steady-state substrate flux and biofilm thickness for S greater than S_min. An example is provided to demonstrate the use of the steadystate model.     

Novel differential elimination method for determining kinetic coefficients under substrate self-inhibition

A differential elimination method (DEM) is developed to determine the kinetic coefficients for substrate self-inhibition. Finite differentiation of the equation eliminates either K_I or K_S, which enables the equation to be linearized so that [^(\textq)] {\hat{\text{q}}} , K_S, and K_I can be estimated without using nonlinear least square regression (NLSR). The DEM options that eliminate K_I or K_S computed the parameter values exactly when the data did not contain any errors. If one-point or random errors were not too large, both DEM options worked as well as NLSR when data were acquired with geometric intervals for substrate concentration. The DEM was more accurate for fitting the data for the smallest and largest values of S, but relatively weaker in estimating the observed maximum substrate utilization rate, q_max. The estimates for S_max, the concentration at which the maximum specific substrate utilization rate is observed, were relatively invariant among the methods, even when K_S and K_I differed. When the intervals were arithmetic (i.e., equal intervals of substrate concentration) and the data contained errors, the DEM and NLSR estimated the parameters poorly, indicating that collecting data with an arithmetic interval greatly increases the risk of poor parameter estimation. Parameter estimates by DEM fit very well experimental data from nitrification or photosynthesis, which were taken with geometric intervals of substrate concentration or light intensity, but fit poorly phenol-degradation data, which were obtained with arithmetic substrate intervals. Besides providing a reasonable substitute for NLSR, the DEM also can be used as a tool to diagnose the quality of experimental data by comparing its estimates between the DEM options, or, more rigorously, to those from NLSR.     

Fed-batch sorbitol to sorbose fermentation by A. suboxydans

Batch kinetics for sorbitol to sorbose bioconversion was studied at 20% sorbitol concentration. The culture featured 90% conversion of sorbitol to sorbose in 20 hours. Increasing the initial substrate concentration in the bioreactor decreased the culture specific growth rate. At 40% initial sorbitol concentration no culture growth was observed. The batch kinetics and substrate inhibition studies were used to develop the Mathematical Model of the system. The model parameters were identified using the original batch kinetic data (S _o =20%). The developed mathematical model was adopted to fed-batch cultivation with the exponential nutrient feeding. The fed-batch model was simulated and implemented experimentally. No substrate inhibition was observed in the fed-batch mode and it provided an overall productivity of 12.6?g/l-h. The fed-batch model suitably described the experimentally observed results. The model is ready for further optimization studies.     

Carbon Conversion Efficiency and Limits of Productive Bacterial Degradation of Methyl tert-Butyl Ether and Related Compounds

The utilization of the fuel oxygenate methyl tert-butyl ether (MTBE) and related compounds by microorganisms was investigated in a mainly theoretical study based on the Y_ATP concept. Experiments were conducted to derive realistic maintenance coefficients and K_s values needed to calculate substrate fluxes available for biomass production. Aerobic substrate conversion and biomass synthesis were calculated for different putative pathways. The results suggest that MTBE is an effective heterotrophic substrate that can sustain growth yields of up to 0.87 g g⁻¹, which contradicts previous calculation results (N. Fortin et al., Environ. Microbiol. 3:407-416, 2001). Sufficient energy equivalents were generated in several of the potential assimilatory routes to incorporate carbon into biomass without the necessity to dissimilate additional substrate, efficient energy transduction provided. However, when a growth-related kinetic model was included, the limits of productive degradation became obvious. Depending on the maintenance coefficient m_s and its associated biomass decay term b, growth-associated carbon conversion became strongly dependent on substrate fluxes. Due to slow degradation kinetics, the calculations predicted relatively high threshold concentrations, S_min, below which growth would not further be supported. S_min strongly depended on the maximum growth rate μ_max, and b and was directly correlated with the half maximum rate-associated substrate concentration K_s, meaning that any effect impacting this parameter would also change S_min. The primary metabolic step, catalyzing the cleavage of the ether bond in MTBE, is likely to control the substrate flux in various strains. In addition, deficits in oxygen as an external factor and in reduction equivalents as a cellular variable in this reaction should further increase K_s and S_min for MTBE.     

A novel method for determining the parameters of microbial kinetics

It is conventional to describe the relationship between the specific rate of microbial growth and the concentration of the inhibitory substrate in terms of the Andrews–Edwards equation. A novel method for establishing the constants of this equation is presented. The equation is transformed to a polynomial and the empirical data are approximated by a quadratic polynomial. The results obtained for the biodegradation of phenol in a mixed culture (activated sludge) are discussed.